Call for Papers


Full paper deadline: June 19, 2009, 5pm US/Pacific


The ubiquitous nature of information and communication today is often cited as the cause of many security and privacy problems including identity and reputation management, viruses/worms and phishing/pharming. There is strong evidence, however, that this abundance of information and communication has at least as many security and privacy benefits as costs. Consider for example, the use of machine learning algorithms to detect network  intrusions, crowd-based approaches to anonymous communication and  the use of data mining algorithms to determine content sanitization. All of these efforts benefit from recent advances in AI, which have often been driven by increases in the amount of available data.
To fully realize the security and privacy benefits of today's ubiquitous information, the security community needs expertise in the tools and techniques for managing that information, namely, artificial intelligence technology, and the AI community needs an understanding of security and privacy problems. To facilitate an exchange of ideas between these two communities, we are holding the second workshop in "AISec" in conjunction with the 16th ACM Conference on Computer and Communications Security (CCS), the new field of security and privacy solutions that leverage AI technologies. Our full-day workshop will be a mix of technical papers and position papers with ideas for AISec's future.
Topics of interest include, but are not limited to:
  • Spam detection
  • Botnet detection
  • Intrusion detection
  • Malware identification
  • Insider threat detection
  • Privacy-preserving data mining
  • Inference detection and control
  • Design and analysis of CAPTCHAs
  • Phishing detection and prevention
  • AI approaches to trust and reputation
  • Incentives in security/privacy systems
  • Machine learning techniques for optimizing user experience
  • Vulnerability testing through intelligent probing (e.g. fuzzing)
  • Content-driven security policy management & access control
  • Techniques and methods for generating training and test sets
  • Anomalous behavior detection (e.g. for the purposes of fraud prevention, authentication)

Paper Submission

We invite original research papers describing significant results using AI techniques to address security and/or privacy problems. We also invite position papers discussing the role of AI in security and privacy. Submitted papers may not substantially overlap papers that have been published or that are simultaneously submitted to a journal or conference with proceedings.

Research submissions should be at most 12 pages excluding the bibliography and well-marked appendices using single-column, 11-point font and reasonable margins on letter-size paper, and at most 15 pages total. Committee members are not required to read the appendices, and so the paper should be intelligible without them. Position papers should be at most 6 pages long in total using the same guidelines as above. Submissions need not be anonymized.

Submissions can be made through EasyChair at the following web site:


Submission deadline: June 19, 2009 
Author notifications: August 16, 2009
Camera ready papers due: August 25, 2008 (Firm deadline)
Workshop: November 9, 2009


Authors of accepted papers are expected to give full presentations at the workshop. Proceedings will be published by the ACM.

Program chairs:

  • Dirk Balfanz (Google)
  • Jessica Staddon (Palo Alto Research Center)

Program Committee:

  • Adam Barth (U. C. Berkeley)
  • Alvaro A. Cardenas (U. C. Berkeley)
  • Kamalika Chaudhuri (U. C. San Diego)
  • George Danezis (Microsoft)
  • Luca de Alfaro (U. C. Santa Cruz)
  • Philippe Golle (PARC)
  • Rachel Greenstadt (Drexel)
  • Virgil Griffith (Caltech)
  • Tad Hogg (HP Labs)
  • Marius Kloft (Fraunhofer)
  • Pavel Laskov (Fraunhofer)
  • Barry O'Sullivan (University College, Cork)
  • Lisa Purvis (Xerox)
  • Zulfikar Ramzan (Symantec)
  • Benjamin Rubinstein (U. C. Berkeley)
  • Sal Stolfo (Columbia University)
  • Paul Thompson (Dartmouth)
  • Shobha Venkataraman (AT&T Research)